Predictive patterns of lower urinary tract symptoms and bacteriuria in adults with type 2 diabetes.

Background: Numerous studies demonstrated the risk factors for urological complications in patients with diabetes before sodium-glucose co-transporter 2 inhibitor (SGLT2i) became commercially available. This study aimed to comprehensively investigate urological characteristics in patients with type 2 diabetes (T2DM) after SGLT2i became commercially available. Methods: We examined 63 outpatients with T2DM suspected of bacteriuria based on urinary sediment examinations. Urine cultures were performed, and lower urinary tract symptoms (LUTS) were assessed via questionnaires. Patients with bacteriuria were assessed using ultrasonography to measure post-void residual volume (PVR). Utilizing demographic and laboratory data, a random forest algorithm predicted LUTS, bacteriuria, and symptomatic bacteriuria (SB). Results: Thirty-two patients had LUTS and 31 had bacteriuria. High-density lipoprotein cholesterol level was crucial in predicting LUTS, while age was crucial in predicting bacteriuria. In predicting SB among patients with bacteriuria, creatinine level and estimated glomerular filtration rate were crucial. Our models had high predictive accuracy for LUTS (area under the curve [AUC] = 0.846), followed by bacteriuria (AUC = 0.770) and SB (AUC = 0.938) in receiver operating characteristic curve analysis. These predictors were previously reported as risk factors for urological complications. Although SGLT2i use was not an important predictor in our study, all SGLT2i users with bacteriuria had SB and exhibited higher PVR compared to non-SGLT2i users with bacteriuria. Conclusion: This study's random forest model highlighted distinct essential predictors for each urological condition. The predictors were consistent before and after SGLT2i became commercially available. Supplementary Information: The online version contains supplementary material available at 10.1007/s13340-023-00687-1.

Pregnancy and delivery in an advanced cancer survivor with immune checkpoint inhibitor-induced type 1 diabetes: a case report.

PURPOSE: Given the rarity and elderly onset of immune checkpoint inhibitor (ICI)-induced type 1 diabetes (ICI-T1DM), cases leading to delivery are rare. METHOD: To our knowledge, this is the first case report of childbirth in a patient with ICI-T1DM after cancer survival. A 32-year-old woman was started on Nivolumab for metastatic parotid cancers one year after total parotidectomy. RESULT: The patient developed ICI-T1DM after 43 cycles and started multiple daily insulin therapy and self-monitoring of blood glucose. Complete response was maintained for 2 years by nivolumab, and she finished nivolumab in 77 cycles to attempt pregnancy. During the follow-up period, she began using a sensor-augmented pump (SAP). She had undetectable serum and urinary C-peptide when she started SAP. Her HbA1c level decreased from 7.8 to 6.6% without increasing hypoglycemia in one year. The patient remained in complete response after ICI discontinuation, and embryo transfer was initiated. Pregnancy was confirmed after a second embryo transfer (21 months after ICI discontinuation). At 36 weeks and 6 days, an emergency cesarean section was performed due to the onset of preeclampsia. The baby had hypospadias and bifid scrotum but no other complications or neonatal intensive care unit admission. CONCLUSION: Because ICI discontinuation and ICI-T1DM carry risks for the patient and child, the decision regarding pregnancy warrants careful consideration. Diabetologists should collaborate with patients and other clinical departments to develop a treatment plan for childbirth.

Alternative splicing events as peripheral biomarkers for motor learning deficit caused by adverse prenatal environments.

Severity of neurobehavioral deficits in children born from adverse pregnancies, such as maternal alcohol consumption and diabetes, does not always correlate with the adversity's duration and intensity. Therefore, biological signatures for accurate prediction of the severity of neurobehavioral deficits, and robust tools for reliable identification of such biomarkers, have an urgent clinical need. Here, we demonstrate that significant changes in the alternative splicing (AS) pattern of offspring lymphocyte RNA can function as accurate peripheral biomarkers for motor learning deficits in mouse models of prenatal alcohol exposure (PAE) and offspring of mother with diabetes (OMD). An aptly trained deep-learning model identified 29 AS events common to PAE and OMD as superior predictors of motor learning deficits than AS events specific to PAE or OMD. Shapley-value analysis, a game-theory algorithm, deciphered the trained deep-learning model's learnt associations between its input, AS events, and output, motor learning performance. Shapley values of the deep-learning model's input identified the relative contribution of the 29 common AS events to the motor learning deficit. Gene ontology and predictive structure-function analyses, using Alphafold2 algorithm, supported existing evidence on the critical roles of these molecules in early brain development and function. The direction of most AS events was opposite in PAE and OMD, potentially from differential expression of RNA binding proteins in PAE and OMD. Altogether, this study posits that AS of lymphocyte RNA is a rich resource, and deep-learning is an effective tool, for discovery of peripheral biomarkers of neurobehavioral deficits in children of diverse adverse pregnancies.

Successful introduction of sensor-augmented pump therapy in a patient with diabetes and needle phobia: A case report.

Needle phobia is a specific phobia classified as an anxiety disorder in the Diagnostic and Statistical Manual of Mental Disorders-5, and can be a serious problem for patients requiring insulin injections. However, there have been few reports to date on the management of adults with diabetes and needle phobia. We here report a case of a woman with pancreatic diabetes who developed needle phobia and could no longer perform self-injections. She started to use a sensor-augmented pump (SAP), and was able to perform a puncture for the insulin pump and the continuous glucose monitoring sensor by herself. The SAP treatment achieved self-management, better glycemic control, and high treatment satisfaction quantified using the Diabetes Treatment Satisfaction Questionnaire in this patient. Our case suggests the therapeutic potential of SAP in adults with needle phobia and diabetes requiring insulin therapy.

Maternally inherited diabetes and deafness complicated by mesangial galactose-deficient IgA1 deposits: a case report.

BACKGROUND: Maternally inherited diabetes and deafness (MIDD), a mitochondrial genetic disorder, typically affects the kidneys and results in end-stage renal disease. Early diagnosis of MIDD is challenging when renal manifestations precede other key clinical features such as diabetes and deafness and/or when the disease is complicated by other renal pathologies. CASE PRESENTATION: Here, we present the case of a 33-year-old Japanese woman who had initially been diagnosed with IgA nephropathy but was found to have MIDD 6 years later. Two renal biopsies were conducted six years apart. While assessment of the first biopsy specimen with the monoclonal antibody (KM55) revealed mesangial IgA deposits (containing the galactose-deficient IgA1 variant [Gd-IgA1]), examination of the second specimen showed no mesangial IgA deposits and newly-developed glomerular global scleroses and tubular damage. Granular swollen epithelial cells (GSECs), characterised by abnormal mitochondria, were observed among the tubules and collecting ducts in both biopsy specimens. Mitochondrial DNA analysis revealed an m.3243A > G mutation. CONCLUSIONS: We rediscovered the usefulness of GSECs as a pathologically distinctive feature of mitochondrial nephropathy and reviewed the literature regarding MIDD complicated by mesangial IgA deposition. Furthermore, we demonstrate that the mesangial IgA deposits in this patient consisted of the galactose-deficient IgA1 variant. The monoclonal antibody (KM55) might be a useful tool to distinguish IgAN from latent IgA deposits.